1. Field
Various features relate to radiation microdosimeters, and more specifically, to solid state microdosimeters that correlate to biological tissue structures.
2. Background
Classical radiation absorbed dosimetry operates to determine the average energy deposited per unit mass, J/kg, but cannot predict the radiobiological effects in biological tissue for the detected radiation. Early attempts at understanding radiation effects on tissue recognized that knowledge of the energy distribution at a scale comparable to the structures affected by irradiation was essential, and hence knowledge of the energy distribution at the cellular level and even DNA level. Consequently, the study of radiation effects on living cells or cell components is called “microdosimetry.”
One of the factors affecting local energy deposition is termed “Linear Energy Transfer” (LET). LET is the linear density of energy lost by an ionizing particle travelling through matter. For example, it may be the loss of energy per unit distance along the path of radiation, especially the path of charged particles. With micro-sized targets, deterministic energy deposition becomes stochastic and depends on the target size and spatial pattern of energy deposited by ionizing radiation (e.g., charged particles). It limits the correlation of the LET approach with radiobiological effects.
There are several reasons for the limitations in the LET concept. First, the delta ray distribution and its relationship to spatial dose distributions are not adequately accounted for in most analyses. Also, particles with different velocities and charges can have the same LET but the particle velocity largely determines the energy distribution of delta rays. In microscopic volumes, the delta ray distribution may be a significant factor in the spatial distribution of energy, particularly at higher particle energies and smaller target tissue sizes. Further, LET is a non-stochastic average quantity, and it does not account for the random fluctuations in energy deposition which manifests as the clustering of energy deposition and range straggling of radiation particles. This variance due to straggling may exceed the path length variations at high particle energies and smaller tissue sizes.
These limitations in LET lead to the formulation of a set of measurable stochastic quantities, which produce the fundamental basis for the field of microdosimetry. Microdosimetry requires instrumentation for measurements of energy deposited in a cellular size or smaller. Instruments to approximate such measurements were developed in the 1940's, such as the low pressure gas proportional counter, also referred to as the “Rossi” counter. This dosimeter is still one of the most common radiation dosimeters, especially in a form known as a “Tissue-Equivalent Proportional Counter” (TEPC). A TEPC uses low-pressure gases, usually of a type that mimics tissue equivalent compounds, and may be surrounded by similar tissue-equivalent materials.
TEPCs have several shortcomings. First, TEPCs require a gas supply system that is inconvenient in many portable applications. Second, TEPCs are relatively large (e.g., 1 cm or larger in diameter), which severely limits the spatial resolution of any detected radiation. Third, TEPCs require high voltages, for example, up to 2,000 volts or more is commonplace. As such, TEPCs are relatively power-hungry devices that cannot be used in a passive mode for weeks or months at a time, since a TEPC cannot record radiation events without power. Fourth, TEPCs suffer from the “wall effect” and other size-related problems since they are very large compared to tissue cells and tissue cell components. This leads to artifacts in the analysis of their microdosimetry spectra. Finally, and most notably, very large volume correction factors are required to compensate for the difference between the TEPC volume (i.e., testing space volume used by the TEPC) and a tissue structure volume (e.g., cell volume) that the TEPC is being used to estimate the radiation energy deposited within. Such a correction factor may be, for example, of the order of 18,000 times or more.
Microdosimetric spectra can be converted to radiobiological characteristics of the radiation field by convolution with a quality coefficient Q over the range of lineal deposited energies, which reflects increasing probability of cell inactivation with increasing lineal event energy. The coefficient Q is determined by the International Commission on Radiation Units and Measurements (ICRU) and based on experimental in-vitro cell survival measurements. Its analytical values are tabulated in Table 1 as a function of LET, the unrestricted linear energy transfer in water.
TABLE 1Quality Coefficient-Q (LET)LET (keV/μm)Q (LET) <10110-100(0.32 × LET) − 2.2>100300/(LET)0.5The coefficient Q is thus a measure of the main difference between absorbed dosimetry and equivalent (radiobiological) dosimetry of radiation fields.
In addition to gas based TEPC radiation measurement devices, dosimetry systems may also utilize semiconductor detectors (e.g., solid state detectors). Solid state detectors allow for the fabrication of small sensitive volume (SV) sizes because of the availability of integrated circuit technology. SV refers to a volume that absorbs radiation energy. In some situations nanodosimetry is used instead of microdosimetry. In nanodosimetry, the small SV of the detector is used to measure absorbed dose or dose rate but with ultra-high spatial resolution. For example, metal oxide semiconductor field-effect-transistors (MOSFET) detectors (which have a very small SV of a few hundred nanometer size) are able to measure absorbed doses with submicron spatial resolution. Such detectors, however, cannot distinguish the energy deposited in the SV due to a particular event. Instead, the output signal represents the integral of many events depositing energy in the SV. This limitation also occurs with many solid state detectors, such as dosimetric diodes working in current mode, thermo-luminescent dosimeters (TLDs), and film.
Passive solid state detectors can be used to some extent in microdosimetry. For example, glow peaks in some TLDs are sensitive to the LET of particles that are associated with energy deposition on the micron level. These detectors are not a suitable substitution for TEPCs, as they do not have sensitive LET resolution and cannot be used in real time dosimetry.
A passive microdosimetry detector (e.g., '199 dosimeter) disclosed in U.S. Pat. No. 5,596,199 records the energy deposition of incident radiation using an array of microstructure non-volatile memory devices. The charge from incident charged particles is stored in an electrically insulated (floating) gate of micron or submicron scale SV of a floating gate avalanche injection metal-oxide-semiconductor (FAMOS) transistor. When this charge exceeds a threshold level, the state of the memory cell changes. The number of cells that have changed state is equal to the number of events that have deposited energy above the threshold. A predetermined initial charge is stored in each cell, which makes the charge increment required to change the state of the cells variable. This is claimed to provide a spectroscopy of the deposited energies, but it is a discreet spectroscopy rather than analogue or real spectroscopy. There can be uncertainty in the cause of the change-of-state resulting from a single event in the SV, or due to several consecutive events, thereby giving an incorrect indication of the radiation field. Owing to the passive mode of operation, the charge deposited in the SV is therefore less than on a floating gate. The charge deficit due to recombination depends on the LET of the particle. Recombination of charge in the gate oxide is well known in MOSFET detectors, and reduces the utility of MOSFET detectors for dosimetry in proton and heavy ions fields (even in an active mode). The '199 microdosimeter is designed principally to distinguish the gamma and neutron components of a radiation field, but it can only with difficultly obtain dose equivalent using the weighting coefficient Q in arbitrary radiation fields as recommended by the ICRU.
Another approach, based on the parallel connection of micron scale semiconductor detectors, such as p-n junctions, provides an active array of micron scale SVs. In this approach, reverse biased semiconductor detectors with micron scale semiconductor (e.g., silicon) SVs are connected to a nuclear spectroscopy system. The small area of the array of p-n junctions allows pile up to be avoided, provided that charge is generated in a single SV only. This condition does not hold, however, if the charged particle traverses an SV in a direction substantially parallel to the surface of the semiconductor array. In such cases energy can be deposited in two SVs simultaneously, providing a greater charge than if it was deposited in a single SV. Spectroscopy information can be converted to dose equivalent using a weighting factor recommended by the ICRU. This technique has been demonstrated using planar arrays of p-n junctions of SRAMs with an SV size of 44×44×3 microns. Applications of such planar arrays of p-n junctions for regional microdosimetry are limited owing to uncertainty in the average chord, charge collection efficiency within the SV, over-layers, and shape of the SV.
Increasing the total area of the p-n junction array leads to increases in the noise owing to an increase in capacitance that reduces the minimal LET detected by the microdosimeter. A segmentation approach with several parallel readout spectroscopy channels has been suggested to reduce the noise of the microdosimeter. This method has been demonstrated in the separation of gamma/neutron field without any qualitative or quantitative (dose equivalent) characterization of the radiation field.
Charge collection spectroscopy in a micron-size array of planar p-n junctions (e.g., SVs) of a memory chip (e.g., SRAM) strongly depends on the fabrication technology, the angle of incidence of the radiation, and the SV shape. Hence, interpretation of the measured spectra for conversion to dose equivalent values is complex. A solid state semiconductor microdosimeter based on a parallel array of p-n junctions for measurements of tissue equivalent microdosimetric spectra has also been reported. The viability of measuring integral dose and microdosimetric spectra simultaneously at the same point in a water phantom in fast neutron therapy beam has also been demonstrated.
Cells may be considered the fundamental component of life. Therefore, whole-body radiation exposure measurements may be useful in warning of generic radiation exposure, but it is the radiation absorbed by the body's cells that is the essential metric in measuring radiation damage to life forms. Traditional methods of measuring radiation safety such as using TPECs or TLDs are seriously limited because of the large scaling factor that has to be used (e.g. on the order 104 or more) in order to estimate the radiation energy deposited in a cell or a cell component. This correction which scales the measured energy deposited to that which would be absorbed by an actual cell is called the Radiation Detector Correction Factor (RDCF). Reducing the RDCF helps increase the accuracy of measurements that determine the actual radiation energy absorbed by a cell.
Note that non-isotropic radiation may be poorly assessed by planar arrays of detectors because different trajectories will yield inconsistent detector signals depending on the geometry of the array to the radiation path. Thus, there is a need to build detectors that mimic the substance and dimensions of cells that will allow the closest approximation to assessing radiation deposition in cells, and make the RDCF approach the ideal value of 1.0 (no correction needed).
The energy deposited in materials is strongly dependent on the availability of conduction electrons, and different tissues absorb energy depending, in part, on their electrical characteristics. Also, for some tissues such as bone, the high relative abundance of high atomic number materials such as calcium will have a significant effect on the energy absorbed. Thus, there is a need to build detectors that can mimic the variation in electrical conductivity of different cells and thereby reduce the RDCF on a cell-type basis.